Dự đoán cường độ chịu nén của chất kết dính sử dụng một số phế phẩm làm việc trong môi trường nhiệt độ cao

The increasing demand for construction materials and the environmental impact of traditional cement production necessitate the exploration of sustainable alternatives. Concrete structures, while widely used, are susceptible to significant degradation when exposed to high temperature environments, underscoring the critical need for binder materials with enhanced thermal resistance. This study addresses this challenge by investigating the use of industrial waste products, specifically fly ash (FA) and finely ground clay tile (FGT), as partial replacements for Portland cement. The primary objective is to develop a robust prediction model for the compressive strength of these blended binders under varying thermal conditions, leveraging the capabilities of artificial neural network (ANN) technology to optimize material design and performance for high-temperature applications.

Researchers and academics in civil engineering, materials science, and computational modeling; engineers and professionals involved in concrete technology, sustainable construction, and design of structures exposed to high temperatures.

This research presents an artificial neural network (ANN) model designed to accurately predict the compressive strength of binder composites consisting of Portland cement partially replaced by industrial waste materials: fly ash (FA) and finely ground clay tile (FGT). The study was motivated by the need for sustainable construction solutions and enhanced material performance in high temperature environments, ranging from 25°C to 800°C. A comprehensive dataset of 42 sample groups, incorporating varying FA and FGT replacement ratios (10-40% by weight) and diverse temperature exposures, was utilized to train, validate, and test the ANN model. The model demonstrated remarkable predictive capability with a high correlation coefficient (R = 0.9629), indicating its reliability for estimating mechanical properties under thermal stress. Analysis using Interval Plots revealed that an optimal replacement of 20% of cement with FA and FGT resulted in the highest binder strength. Furthermore, the study elucidated the complex relationship between temperature and compressive strength, showing an initial increase up to 200°C due to drying and densification, followed by a decline at higher temperatures caused by the decomposition of hydration products like C-S-H and Ca(OH)2. This methodology offers a rapid, cost-effective, and efficient approach for material characterization, facilitating the development of durable and environmentally friendly concrete for extreme thermal conditions. The findings have significant implications for optimizing mix designs and promoting the practical application of waste materials in the construction industry.